{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T14:58:59Z","timestamp":1776178739546,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"MCIN\/AEI\/10.13039\/501100011033","award":["Spanish Grant SARAI, PID2020-116540RB-C21"],"award-info":[{"award-number":["Spanish Grant SARAI, PID2020-116540RB-C21"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033","award":["POIR.04.01.04-00-0056\/17"],"award-info":[{"award-number":["POIR.04.01.04-00-0056\/17"]}]},{"name":"European Regional Development Fund within the Smart Growth Operational Program 2014\u20132020","award":["Spanish Grant SARAI, PID2020-116540RB-C21"],"award-info":[{"award-number":["Spanish Grant SARAI, PID2020-116540RB-C21"]}]},{"name":"European Regional Development Fund within the Smart Growth Operational Program 2014\u20132020","award":["POIR.04.01.04-00-0056\/17"],"award-info":[{"award-number":["POIR.04.01.04-00-0056\/17"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This work addresses a methodology based on the interferometric synthetic aperture radar (InSAR) applied to analyze and monitor ground-motion phenomena induced by underground mining activities in the Legnica-Glogow copper district, south-western Poland. The adopted technique employs an InSAR processing chain that exploits a stack of Sentinel-1 synthetic aperture radar (SAR) images using a small baseline multitemporal approach. Interferograms with small temporal baselines are first selected, then their network is optimized and reduced to eliminate noisy data, in order to mitigate the effect of decorrelation sources related to seasonal phenomena, i.e., snow and vegetation growth, and to the radar acquisition geometry. The atmospheric disturbance is mitigated using a spatio-temporal filter based on the nonequispaced fast Fourier transform. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against global navigation satellite system (GNSS) measurements. In this context, a significant threat to the built environment is represented by seismic tremors triggered by underground mining activities, which are analyzed using the proposed method to integrate the information gathered by in situ seismometer devices.<\/jats:p>","DOI":"10.3390\/rs14092182","type":"journal-article","created":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T07:08:58Z","timestamp":1651475338000},"page":"2182","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A Multi-Temporal Small Baseline Interferometry Procedure Applied to Mining-Induced Deformation Monitoring"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6121-9485","authenticated-orcid":false,"given":"Riccardo","family":"Palam\u00e0","sequence":"first","affiliation":[{"name":"Geomatics Research Unit, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC-CERCA), Avg Gauss 7, E-08860 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8545-5490","authenticated-orcid":false,"given":"Michele","family":"Crosetto","sequence":"additional","affiliation":[{"name":"Geomatics Research Unit, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC-CERCA), Avg Gauss 7, E-08860 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8954-7963","authenticated-orcid":false,"given":"Jacek","family":"Rapinski","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6254-7931","authenticated-orcid":false,"given":"Anna","family":"Barra","sequence":"additional","affiliation":[{"name":"Geomatics Research Unit, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC-CERCA), Avg Gauss 7, E-08860 Barcelona, Spain"}]},{"given":"Mar\u00eda","family":"Cuevas-Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Geomatics Research Unit, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC-CERCA), Avg Gauss 7, E-08860 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2505-6855","authenticated-orcid":false,"given":"Oriol","family":"Monserrat","sequence":"additional","affiliation":[{"name":"Geomatics Research Unit, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC-CERCA), Avg Gauss 7, E-08860 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2863-0560","authenticated-orcid":false,"given":"Bruno","family":"Crippa","sequence":"additional","affiliation":[{"name":"Department of Geophysics, University of Milan, Via Cicognara 7, I-20129 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1834-3162","authenticated-orcid":false,"given":"Natalia","family":"Kotulak","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0929-4300","authenticated-orcid":false,"given":"Marek","family":"Mr\u00f3z","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9932-1810","authenticated-orcid":false,"given":"Magdalena","family":"Mleczko","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Owczarz, K., and Blachowski, J. (2020). Application of DInSAR and spatial statistics methods in analysis of surface dis-placements caused by induced tremors. Appl. Sci., 10.","DOI":"10.3390\/app10217660"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sopata, P., Stoch, T., W\u00f3jcik, A., and Mroche\u0144, D. (2020). Land Surface Subsidence Due to Mining-Induced Tremors in the Upper Silesian Coal Basin (Poland)\u2014Case Study. Remote Sens., 12.","DOI":"10.3390\/rs12233923"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.enggeo.2018.10.013","article-title":"Mapping ground movements caused by min-ing-induced earthquakes applying satellite radar interferometry","volume":"246","author":"Malinowska","year":"2018","journal-title":"Eng. Geol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Witkowski, W.T., \u0141ukosz, M., Guzy, A., and Hejmanowski, R. (2021). Estimation of Mining-Induced Horizontal Strain Tensor of Land Surface Applying InSAR. Minerals, 11.","DOI":"10.3390\/min11070788"},{"key":"ref_5","first-page":"297","article-title":"Identification of the ground movements caused by mining-induced seismicity with the satellite interferometry","volume":"382","author":"Hejmanowski","year":"2020","journal-title":"Proc. Int. Assoc. Hydrol. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Antonielli, B., Sciortino, A., Scancella, S., Bozzano, F., and Mazzanti, P. (2021). Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR\u2014I: Room and Pillar Mine District. Land, 10.","DOI":"10.3390\/land10060653"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mazzanti, P., Antonielli, B., Sciortino, A., Scancella, S., and Bozzano, F. (2021). Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR\u2014II: \u017belazny Most Tailings Dam. Land, 10.","DOI":"10.3390\/land10060654"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1016\/j.proeps.2009.09.166","article-title":"Advanced GNSS technology of mining deformation monitoring","volume":"1","author":"Hong","year":"2009","journal-title":"Procedia Earth Planet. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1007\/s11069-013-0868-7","article-title":"GPS\/terrestrial 3D laser scanner combined monitoring technology for coal mining subsidence: A case study of a coal mining area in Hebei, China","volume":"70","author":"Zhou","year":"2013","journal-title":"Nat. Hazards"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1029\/97RG03139","article-title":"Radar interferometry and its application to changes in the Earth\u2019s surface","volume":"36","author":"Massonnet","year":"1998","journal-title":"Rev. Geophys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A tutorial on synthetic ap-erture radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent scatterers in SAR interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.isprsjprs.2015.10.011","article-title":"Persistent Scatterer Interferometry: A Review","volume":"115","author":"Crosetto","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4035","DOI":"10.1029\/1998GL900033","article-title":"Radar interferogram filtering for geophysical applications","volume":"25","author":"Goldstein","year":"1998","journal-title":"Geophys. Res. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tecto.2011.10.013","article-title":"Recent advances in SAR interferometry time series analysis for measuring crustal deformation","volume":"514\u2013517","author":"Hooper","year":"2012","journal-title":"Tectonophysics"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1109\/TGRS.2011.2124465","article-title":"A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR","volume":"49","author":"Ferretti","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4394","DOI":"10.1109\/TGRS.2015.2396875","article-title":"Improved EMCF-SBAS Processing Chain Based on Advanced Techniques for the Noise-Filtering and Selection of Small Baseline Multi-Look DInSAR Interferograms","volume":"53","author":"Pepe","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1109\/TGRS.2006.872907","article-title":"MST-based stepwise connection strategies for multipass radar data, with application to coregistration and equalization. IEEE Trans","volume":"44","author":"Refice","year":"2006","journal-title":"Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TGRS.2011.2160644","article-title":"Repeat-Pass SAR Interferometry with Partially Coherent Targets","volume":"50","author":"Perissin","year":"2011","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2445","DOI":"10.1007\/s10346-021-01654-0","article-title":"Semi-automated regional classifica-tion of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data","volume":"18","author":"Crippa","year":"2021","journal-title":"Landslides"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7253","DOI":"10.1038\/s41598-018-25369-w","article-title":"Continuous, semi-automatic monitoring of ground deformation using Sentinel-1 satellites","volume":"8","author":"Raspini","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Crosetto, M., Solari, L., Mr\u00f3z, M., Balasis-Levinsen, J., Casagli, N., Frei, M., Oyen, A., Moldestad, D., Bateson, L., and Guerrieri, L. (2020). The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service. Remote Sens., 12.","DOI":"10.3390\/rs12122043"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6259","DOI":"10.1109\/TGRS.2019.2904912","article-title":"The Parallel SBAS Approach for Sentinel-1 Interferometric Wide Swath Deformation Time-Series Generation: Algorithm Description and Products Quality Assessment","volume":"57","author":"Manunta","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Cigna, F., and Tapete, D. (2021). Sentinel-1 Big Data Processing with P-SBAS InSAR in the Geohazards Exploitation Platform: An Experiment on Coastal Land Subsidence and Landslides in Italy. Remote Sens., 13.","DOI":"10.3390\/rs13050885"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Solari, L., Montalti, R., Barra, A., Monserrat, O., Bianchini, S., and Crosetto, M. (2020). Multi-Temporal Satellite Interferometry for Fast-Motion Detection: An Application to Salt Solution Mining. Remote Sens., 12.","DOI":"10.3390\/rs12233919"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Pawluszek-Filipiak, K., and Borkowski, A. (2020). Integration of DInSAR and SBAS techniques to determine mining-related deformations using Sentinel-1 data: The case study of rydultowy mine in Poland. Remote Sens., 12.","DOI":"10.3390\/rs12020242"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5300","DOI":"10.3390\/rs70505300","article-title":"Combination of conventional and ad-vanced DInSAR to monitor very fast mining subsidence with TerraSAR-X data: Bytom City (Poland)","volume":"7","author":"Przylucka","year":"2015","journal-title":"Remote Sens."},{"key":"ref_28","first-page":"92430K","article-title":"The PSIG chain: An approach to Persistent Scatterer Interferometry","volume":"9243","author":"Crosetto","year":"2014","journal-title":"SAR Image Anal. Model. Tech. XIV"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6662","DOI":"10.3390\/rs6076662","article-title":"An Approach to Persistent Scatterer Interferometry","volume":"6","author":"Crosetto","year":"2014","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hanssen, R.F. (2001). Radar Interferometry: Data Interpretation and Error Analysis, Kluwer Academic Publishers.","DOI":"10.1007\/0-306-47633-9"},{"key":"ref_31","unstructured":"Van Leijen, F. (2014). Persistent Scatterer Interferometry Based on Geodetic Estimation Theory. [Ph.D. Thesis, Delft University of Technology]."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2202","DOI":"10.1109\/36.868878","article-title":"Nonlinear Subsidence Rate Estimation Using permanent scatterers in differential SAR interferometry","volume":"38","author":"Ferretti","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","unstructured":"Kunis, S. (2006). Nonequispaced FFT, Generalisation and Inversion. [Ph.D. Thesis, University of Lubeck]."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Fuhrmann, T., and Garthwaite, M.C. (2019). Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion. Remote Sens., 11.","DOI":"10.3390\/rs11030241"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Ulaby, F.T., and Long, D.G. (2014). Microwave Radar and Radiometric Remote Sensing, The University of Michigan Press.","DOI":"10.3998\/0472119356"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MGRS.2018.2873644","article-title":"Phase Unwrapping in InSAR: A Review","volume":"7","author":"Yu","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1109\/36.673674","article-title":"A novel phase unwrapping method based on network programming","volume":"36","author":"Costantini","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1555386.1555388","article-title":"Using NFFT 3\u2014A software library for various nonequispaced fast fourier trans-forms","volume":"36","author":"Keiner","year":"2009","journal-title":"ACM Trans. Math. Softw."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Palama, R., Crosetto, M., Monserrat, O., Barra, A., Cuevas, M., Crippa, B., Rapinski, J., and Mroz, M. (2021, January 11\u201316). Filtering of the atmospheric phase screen in InSAR data using the Nonequispaced Fast Fourier Transform. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9553800"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Navarro, J.A., Tomas, R., Barra, A., Pag\u00e1n, J.I., Reyes-Carmona, C., Solari, R., Vinielles, J.L., Falco, S., and Crosetto, M. (2020). ADAtools: Automatic detection and classification of active deformation areas from PSI dis-placement maps. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9100584"},{"key":"ref_42","first-page":"443","article-title":"Optimal data processing strategy in precise GPS leveling net-works","volume":"10","author":"Stepniak","year":"2013","journal-title":"Acta Geodyn. Geromater."},{"key":"ref_43","first-page":"187","article-title":"Assessment of mining tremor influence on the technical wear of building","volume":"1","author":"Wodynski","year":"2004","journal-title":"Acta Geodyn. Geomater."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Wassie, Y., Mirmazloumi, S.M., Crosetto, M., Palam\u00e0, R., Monserrat, O., and Crippa, B. (2022). Spatio-Temporal Quality Indi-cators for Differential Interferometric Synthetic Aperture Radar Data. Remote Sens., 14.","DOI":"10.3390\/rs14030798"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1945","DOI":"10.5194\/nhess-13-1945-2013","article-title":"Automated classification of Persistent Scatterers Interfer-ometry time series","volume":"13","author":"Berti","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1080\/15481603.2022.2030535","article-title":"Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series","volume":"59","author":"Mirmazloumi","year":"2022","journal-title":"GISci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ansari, H., Rubwurm, M., Ali, M., Montazeri, S., Parizzi, A., and Zhu, X.X. (2021, January 11\u201316). InSAR Displacement Time Series Mining: A Machine Learning Approach. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS 2021), Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9553465"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2182\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:05:22Z","timestamp":1760137522000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2182"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,2]]},"references-count":47,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["rs14092182"],"URL":"https:\/\/doi.org\/10.3390\/rs14092182","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,2]]}}}